Hello,
I am using numpy in conjunction with pyTables. The data that I read in from
pyTables seem to have the following dtype:
p = hdf5.root.myTable.read()
p.__class__
<type 'numpy.ndarray'>
p[0].__class__
<type 'numpy.void'>
p.dtype
dtype([('time', '<f4'), ('obs1', '<f4'), ('obs2', '<f8'), ('obs3', '<f4')])
p.shape
(61230,)
The manner in which I access a particular column is p['time'] or p['obs1'].
I have a couple of questions regarding this data structure: 1) how do I
restructure the array into a 61230 x 4 array that can be indexed using [r,c]
notation? 2) What kind of dtype is pyTables using? How do I create a
similar array that can be indexed by a named column? I tried various ways:
a = array([[1,2],[3,4]], dtype=dtype([('obs1','<f4'),('obs2','<f4')]))
---------------------------------------------------------------------------
<type 'exceptions.TypeError'> Traceback (most recent call last)
p:\AsiaDesk\johngu\projects\deltaForce\<ipython console> in <module>()
<type 'exceptions.TypeError'>: expected a readable buffer object
I did find some documentation about array type descriptors when reading from
files... it seems like these array types are specific to arrays created when
reading from some sort of file / buffer? Any help is appreciated. Thanks!
John
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